Title: Visual place representation and recognition from depth images

Authors: Farah Ibelaiden; Slimane Larabi

Addresses: RIIMA Laboratory, Computer Science Faculty, USTHB University, BP 32 El Alia, Algiers, 16111, Algeria ' RIIMA Laboratory, Computer Science Faculty, USTHB University, BP 32 El Alia, Algiers, 16111, Algeria

Abstract: We propound a new visual positioning method that recognises the previously visited places whose descriptors are stored in a dataset that does not need updates. The descriptor of the unknown location is computed from a depth video acquired by surrounding the depth camera in the scene to build gradually the corresponding 3D map. From which the 2D map is derived and described geometrically based on the architectural features to constitute the query descriptor which is compared to database descriptors in order to deduce the location. The experiments show the efficiency and robustness of the proposed descriptor to scenery changes, light variations and appearance changes.

Keywords: place recognition; depth image; architecture-based descriptor; three dimensional model; two dimensional map.

DOI: 10.1504/IJCVR.2024.140816

International Journal of Computational Vision and Robotics, 2024 Vol.14 No.5, pp.467 - 490

Received: 09 Apr 2022
Accepted: 27 Sep 2022
Published online: 03 Sep 2024 *

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